Software Engineer II / Software Engineer III (Data & BI)

Job Summary

At Guidewire, we transform how the world's PC insurers do business by combining digital, core, analytics, and AI through our cloud data platform. As a Software Engineer 2 (Data BI), you will build trusted data products, reporting datasets, and business intelligence experiences that help teams make informed decisions. You will join PDO - an organization focused on operational excellence, transformative innovation, customer success, and accelerating AI, cloud, and data-platform adoption. Your work will help deliver secure, scalable solutions and measurable value for Guidewire customers.

Growth is shared and shaped by the people we work with and the experiences we create together. You will learn by doing, collaborate with colleagues and stakeholders, and contribute to an inclusive culture that welcomes different perspectives and values every voice. This is an opportunity to grow your technical and professional journey while helping advance Guidewire's mission in a supportive, globally connected environment.

What you will do

Architect, construct, and maintain business intelligence solutions that enable data-informed decision-making across the Guidewire Data Platform.

Engage with stakeholders to understand business needs and translate requirements into clear technical specifications and deliverable analytics solutions.

Design, implement, and tune analytical data models, including star and snowflake schemas, and develop optimized SQL for efficient extraction and transformation.

Develop and support interactive dashboards and analytical reporting using modern BI platforms such as ThoughtSpot.

Establish testing and validation standards that promote data integrity, accuracy, completeness, and reliability.

Engineer reporting datasets and ETL/ELT transformation pipelines using AWS cloud technologies, with a focus on Amazon Redshift.

Use Python or suitable programming languages to automate validation checks, data-quality processes, and repeatable analytical routines.

Use AI-assisted developer tools, including Claude Code and Gemini, to support development, debugging, analysis, and technical documentation; review and validate all generated output before production use.

Maintain clear documentation for data models, transformation logic, KPI definitions, dashboards, and operational procedures to support knowledge transfer and reuse.

What you need to succeed

6+ years of experience in business intelligence development or a related engineering role, with a proven track record of successful projects.

Experience developing data, analytics, business intelligence, or reporting solutions in a software engineering or data engineering environment.

Strong SQL skills, including advanced querying (complex joins, window functions, CTEs, aggregations), query optimization, data transformation, and analytical problem-solving.

Experience designing dimensional data models, including star and snowflake schemas.

Experience with cloud-based data platforms and services, preferably AWS and Amazon Redshift.

Experience building dashboards and reports with a modern BI platform; ThoughtSpot experience is a plus.

Proficiency in Python or another programming language used for automation and data processing.

Familiarity with ETL/ELT development, data-quality testing, validation, and deployment practices.

Working knowledge of Git/GitHub, code reviews, and collaborative software development workflows.

Ability to communicate clearly with technical and non-technical stakeholders and convert business requirements into maintainable solutions.

Strong analytical judgment, attention to detail, and commitment to data integrity.

Willingness to learn new technologies, including AI-assisted development tools, and apply appropriate technical review and quality controls.

Disclaimer: This job posting and location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.